bims-glumda Biomed News
on CGM data in management of diabetes
Issue of 2026–08–23
sixteen papers selected by
Mott Given



  1. JAMA Netw Open. 2026 Aug 03. 9(8): e2629291
       Importance: Interest in use of continuous glucose monitoring (CGM) in the hospital is increasing, yet clear guidance on the optimal implementation of CGM glucose alerts is lacking. It also remains unclear if alerts themselves or the fact that sensor values are available in real time are the main reason for improved glucose outcomes observed with inpatient CGM use.
    Objective: To determine the incremental value of CGM threshold and predictive alerts for glucose management among hospitalized adults with diabetes.
    Design, Setting, and Participants: This single-center, open-label, randomized clinical trial was conducted between April 15 and December 9, 2024, at a tertiary hospital. Eligible participants were adults with type 1 or type 2 diabetes admitted to endocrinology wards.
    Interventions: Participants were randomly assigned (1:1:1) to receive 1 of the 3 CGM alert strategies: all alerts off (n = 178), threshold alerts only (n = 177), or threshold plus predictive alerts (n = 178).
    Main Outcomes and Measures: The primary outcome was the percentage of time within the target glucose range of 70 to 180 mg/dL (time in range [TIR]). The primary analysis was conducted on a modified intention-to-treat basis, including all randomized participants except those who were subsequently confirmed not to meet the eligibility criteria.
    Results: Among the 533 randomized participants, 331 (62.1%) were male, the mean (SD) age was 62 (12) years, and the mean (SD) hemoglobin A1c level was 9.2% (2.1%). The mean (SD) TIR during hospitalization was significantly higher among the group with threshold alerts on than the group with all alerts off (75.1% [16.6%] vs 71.2% [18.1%]; adjusted mean difference, 3.9% [95% CI, 0.1%-7.8%]; Holm-adjusted P = .04). Moreover, time above range (>180 mg/dL) was lower in the group with threshold alerts on than in the group with all alerts off (-3.9% [95% CI, -7.1% to -0.7%]), whereas time below range (<70 mg/dL) did not differ between groups (-0.04% [95% CI, -0.3% to 0.2%]). No differences in primary and secondary outcomes were observed between the group with threshold plus predictive alerts and either of the other 2 groups.
    Conclusions and Relevance: In this randomized clinical trial of hospitalized adults with diabetes, CGM threshold glucose alerts modestly improved glycemic control compared with CGM use without alerts. The addition of predictive alerts did not confer further glycemic benefit beyond threshold alerts alone. Future development of integrated clinical decision support systems or automated insulin delivery technologies may further enhance the effectiveness of CGM among hospitalized patients.
    Trial Registration: ClinicalTrials.gov Identifier: NCT05941286.
    DOI:  https://doi.org/10.1001/jamanetworkopen.2026.29291
  2. Front Endocrinol (Lausanne). 2026 ;17 1901834
       Objective: Impaired islet β-cell function is the core mechanism underlying type 2 diabetes mellitus (T2DM). This study investigated the association between islet β-cell function and time in range (TIR) in patients with T2DM, providing a reference for individualized clinical treatment.
    Methods: This retrospective cross-sectional observational l study included 1,160 patients with confirmed T2DM. Participants underwent continuous glucose monitoring (CGM). TIR >70% was defined as achieving the glycemic target. Subjects were divided into three groups based on TIR levels (<70%, 70%-84%, and ≥85%). The β-cell function index HOMA2-β was calculated using the Homeostasis Model Assessment 2 as the core research indicator.
    Results: The high TIR group had significantly higher HOMA2-β (P < 0.001). Multiple linear regression analysis showed a robust positive correlation between HOMA2-β and TIR after adjusting for covariates (β = 0.402, 95% CI: 0.358-0.447, P < 0.001). Restricted cubic spline (RCS) analysis revealed a significant nonlinear relationship between HOMA2-β and TIR (P for nonlinearity < 0.001). TIR increased with rising HOMA2-β, but the rate of increase gradually slowed. Specifically, when HOMA2-β increased from approximately 10% to 100%, the predicted TIR rose rapidly from about 38% to approximately 96%, representing an increase of 58%. Sensitivity analysis using HOMA2-β calculated from fasting C-peptide instead of fasting insulin yielded consistent conclusions.
    Conclusion: A significant, nonlinear association exists between islet β-cell function HOMA2-β and TIR. TIR levels increase progressively with higher HOMA2-β. Although the cross-sectional design precludes causal inference, these findings provide important reference values for clinical decision-making.
    Keywords:  HOMA2-β; beta-cell function; continuous glucose monitoring (CGM); time in range (TIR); type 2 diabetes
    DOI:  https://doi.org/10.3389/fendo.2026.1901834
  3. Diabetes Care. 2026 Aug 17. pii: dc260886. [Epub ahead of print]
       OBJECTIVE: To identify and characterize daily and weekly patterns in glycemic management in longitudinal real-world continuous glucose monitoring (CGM) data from people with diabetes to enhance clinical interpretation and support more effective personalized diabetes management.
    RESEARCH DESIGN AND METHODS: This observational, retrospective study used two independent, multiyear, real-world CGM cohorts (T1DiabetesGranada and Connected Pen), comprising 86,779 participants with diabetes. Their mean age (SD) was 40.3 (15.8) and 44.0 (15.9), respectively, and there was a total of 21,011,021 measurement days. Weekly variations in CGM metrics and bolus insulin dose were examined using linear mixed-effects models, and daily temporal patterns were assessed.
    RESULTS: Weekly and daily glycemic patterns emerged. Mid-week time in range was consistently higher (e.g., Wednesday: +0.96 percentage points [%-points]; 95% CI 0.93-0.99; P < 0.001), with deterioration during weekends and Mondays (e.g., Sunday: -1.74%-points; 95% CI -1.77, -1.72; P < 0.001), mirrored by shifts in other CGM metrics. Bolus insulin dose increased on weekend days (e.g., Sunday: +0.69 units; 95% CI 0.64-0.74; P < 0.001). Daily analyses revealed distinct diurnal profiles, with the most favorable glycemic control during morning and midday hours on weekdays and consistently poorer control during evening and nighttime periods, particularly on weekends.
    CONCLUSIONS: Daily and weekly glycemic patterns revealed statistically robust and consistent temporal variations in glycemic control across two large real-world cohorts. Although the magnitude of these differences was small, the findings provide novel population-level evidence and underscore the value of longer-term CGM perspectives in routine care.
    DOI:  https://doi.org/10.2337/dc26-0886
  4. Lancet Reg Health Eur. 2026 Oct;69 101806
       Background: Continuous glucose monitoring (CGM) improves glycaemic management in adults with type 1 diabetes (T1D), but may be associated with weight gain. We assessed changes in body weight and HbA1c after CGM initiation and characterized weight-glycemia trajectories.
    Methods: We retrospectively analysed 4178 adults with T1D initiating CGM from the DPV registry (DPV-CGM; n = 2104) and a pooled Belgian cohort (BE-CGM; n = 2074). Outcomes over 24 months were evaluated using paired t-tests and group-based multi-trajectory modelling. In DPV, CGM initiators were compared with matched controls without CGM (n = 2104; matched for sex, age, diabetes duration, baseline weight, and HbA1c).
    Findings: After 24 months, mean body weight increased by 1.8 kg [95% CI: 1.5; 2.0] in DPV-CGM and 1.0 kg [0.8; 1.2] in the BE-CGM cohort, while HbA1c decreased by -0.2% [-0.1; -0.2] and -0.1% [-0.03; -0.1], respectively (all p < 0.0001). In DPV-controls, weight increased by 1.2 kg [0.9; 1.5] (p < 0.01) and HbA1c decreased by 0.06% [-0.001; -0.11] (p = 0.05). Three trajectories were identified. The first showed modest weight gain with HbA1c improvement: 147/2104 (7.0%) DPV-CGM vs 99/2104 (4.7%) DPV-controls, and 411/2074 (19.8%) in BE-CGM. The second, largest group, showed stable weight and HbA1c: 1773/2104 (83.2%) DPV-CGM vs 1612/2104 (74.7%) controls in DPV-controls, and 1447/2074 (69.8%) in BE-CGM. The third, an unfavourable trajectory characterized by substantial weight gain (≈8 kg) with stable HbA1c, included 184/2104 (9.9%) DPV-CGM vs 393/2104 (20.5%) DPV-controls, and 216/2074 (10.4%) in BE-CGM (ꭓ2 p < 0.01).
    Interpretation: CGM initiation was associated with modest weight gain and improved HbA1c. Compared with matched controls, CGM users were less likely to belong to the unfavourable weight gain with stable HbA1c trajectory, which occurred in 9.9% vs 20.5%, respectively.
    Funding: Innovative Medicines Initiative2 Joint Undertaking under grant agreement No. 875534.
    Keywords:  CGM; HbA1c; Individual-level; Type 1 diabetes; Weight
    DOI:  https://doi.org/10.1016/j.lanepe.2026.101806
  5. Diabetes Technol Ther. 2026 Aug 21. 15209156261481005
       BACKGROUND: Contemporary data on the natural history of mild non-proliferative diabetic retinopathy (NPDR) in adults with type 1 diabetes managed under intensive therapy and continuous glucose monitoring (CGM) are limited. We aimed to characterize the long-term evolution of mild NPDR in this modern care setting and to explore clinical and glycemic factors associated with regression or progression, including CGM-derived metrics.
    METHODS: We conducted a retrospective cohort study of adults with type 1 diabetes and mild NPDR identified by digital fundus photography within a screening program between 2018 and 2020. Participants underwent follow-up retinal evaluation after approximately 5 years. Retinopathy outcomes were classified as regression (absence of retinopathy), stability (persistent mild NPDR), or progression (moderate/severe NPDR and/or diabetic macular edema [DME]). Clinical, biochemical, and glycemic variables, including HbA1c and CGM-derived metrics, were collected. Multivariable logistic regression identified factors independently associated with regression of mild NPDR.
    RESULTS: Among 113 participants (median age 39 years; median diabetes duration 21 years), regression occurred in 57.5%, 31.0% remained stable, and 11.5% progressed. Lower HbA1c at follow-up was observed in participants with regression compared with those without. Several CGM-derived metrics, including time in range and glucose management indicator, were associated with regression in univariate analyses; however, these associations were not independent of HbA1c due to strong collinearity. In multivariable analysis, lower HbA1c was the only independent predictor of regression.
    CONCLUSIONS: In this real-world screening-based cohort of adults with T1D, mild NPDR demonstrated a highly dynamic course, with more than half of patients experiencing regression over 5 years. Overall glycemic control, reflected by HbA1c, was the primary determinant of regression. CGM-derived metrics did not provide additional predictive value beyond HbA1c in this setting. These findings highlight the potential reversibility of early diabetic retinopathy under contemporary care and underscore the importance of intensive long-term glycemic management.
    Keywords:  HbA1c; continuous glucose monitoring; diabetic retinopathy regression; glycemic control; type 1 diabetes
    DOI:  https://doi.org/10.1177/15209156261481005
  6. Front Endocrinol (Lausanne). 2026 ;17 1891725
       Background: To evaluate the relationship between residual islet β-cell function assessed by fasting C-peptide (FCP) and continuous glucose monitoring (CGM) metrics in patients with type 1 diabetes mellitus (T1DM), and to clarify the impact of residual islet β-cell function on glycemic control in T1DM.
    Methods: A retrospective study was conducted including 112 patients with T1DM [68 classic T1DM, 44 latent autoimmune diabetes in adults (LADA)] hospitalized from January 2023 to December 2025. All patients wore CGM devices for ≥7 days. Participants were stratified into four groups by FCP quartiles. Spearman correlation, restricted cubic spline (RCS) regression, and multivariable linear regression with progressive adjustment for confounders were used to evaluate associations between FCP and CGM-derived metrics, including time in range (TIR), time above range (TAR), and mean glucose (MG). Subgroup and interaction analyses were performed by diabetes subtype. Sensitivity analyses included quartile-based categorization, exclusion of LADA patients, and exclusion of those with diabetes duration ≥10 years.
    Results: In this retrospective study, higher FCP levels were significantly associated with favorable CGM-derived metrics, including increased TIR, decreased TAR, and lower MG (all P < 0.001). These associations persisted after multivariable adjustment for sex, age, disease duration, BMI, insulin dosage, and glucose coefficient of variation (CV). RCS analysis revealed significant nonlinear dose-response relationships, with pronounced glycemic improvements at lower FCP concentrations and plateau effects at higher levels. LADA patients exhibited higher FCP levels, longer TIR, and lower TAR compared with classic T1DM (all P < 0.05). Subgroup analyses demonstrated consistent FCP-CGM associations in both subtypes without significant interaction (all P for interaction > 0.05). Sensitivity analyses confirmed robust associations after excluding LADA patients or those with disease duration ≥10 years. Shorter disease duration and lower daily insulin requirements correlated with higher FCP levels.
    Conclusion: Residual β-cell function is independently associated with improved CGM-derived metrics (increased TIR, decreased TAR, and lower MG) in both classic T1DM and LADA. Preserved C-peptide secretion correlates with shorter disease duration and lower daily insulin requirements. These findings highlight the importance of protecting residual β-cell function to achieve glycemic stability and reduce exogenous insulin dependence in T1DM.
    Keywords:  continuous glucose monitoring; fasting C-peptide; residual β-cell function; time in range; type 1 diabetes mellitus
    DOI:  https://doi.org/10.3389/fendo.2026.1891725
  7. Bull Math Biol. 2026 Aug 18. pii: 158. [Epub ahead of print]88(9):
      Diabetes represents a significant global health challenge, underscoring the need for enhanced methodologies in glycemic monitoring and risk assessment. Static biomarkers, including fasting plasma glucose and glycated hemoglobin, may have limitations in capturing the temporal variations and individual heterogeneities inherent in glucose regulation. Continuous glucose monitoring (CGM) offers a high-resolution approach that may facilitate timely metabolic categorization. However, there is a notable scarcity of modeling frameworks that integrate CGM data while maintaining both interpretability and predictive accuracy. This study proposes an integrated analytical framework that amalgamates CGM data-driven classification of glucose response with a hybrid modeling approach that combines dynamical systems and deep learning methodologies for personalized glucose regulation assessments. A cohort of 44 adults was enrolled and followed up on an individual basis for 7 to 14 days, and typical daily glucose profiles were derived through dynamic time warping. K-shape clustering analysis was employed to identify significant glucose response subtypes, differentiating participants into three categories: health, prediabetes, and diabetes based on CGM-derived indicators. We subsequently developed an integrated hybrid model that synergizes a dietary stimulation glucose-insulin dynamical model with a long short-term memory residual network. This hybrid model demonstrated substantially improved accuracy, achieving a root mean square error (RMSE) of 6.61 and a coefficient of determination ( R2 ) of 0.91. The glucose-insulin dynamical model effectively elucidates the physiological mechanisms underlying postprandial glucose-insulin regulation. The findings of this study emphasize the utility of CGM-derived glucose phenotyping and hybrid predictive models as viable tools for individualized metabolic risk assessment. Additionally, they contribute to the early identification of dysglycemia and establish a practical framework for precision glycemic management.
    Keywords:  Deep learning; Dynamical models; Glucose subtyping; Glycemic prediction; Hybrid modeling
    DOI:  https://doi.org/10.1007/s11538-026-01678-4
  8. Intern Med J. 2026 Aug 16.
      Metformin has gained attention as a potential adjunct therapy in pregnant women with type 1 diabetes mellitus (T1DM), although evidence is limited. We present the first reported experience of metformin use in pregnant women living with T1DM who used continuous glucose monitoring to monitor glycaemic outcomes. In our multicentre case series, metformin use was associated with an increased time in range and reduced glycaemic variability, supporting potential use in pregnant women with T1DM.
    Keywords:  continuous glucose monitoring; metformin; pregnancy; type 1 diabetes
    DOI:  https://doi.org/10.1111/imj.70607
  9. Diabetes Technol Ther. 2026 Aug 20. 15209156261479816
       BACKGROUND: Continuous glucose monitoring (CGM) accuracy in critically ill patients may be influenced by altered physiology and concurrent therapies. We assessed independent associations between sensor wear time, arterial blood glucose (ABG), noradrenaline-equivalent (NE) dose, erythrocyte volume fraction, pH, lactate, body-mass index and dialysis to CGM performance (Dexcom G6®) in this setting.
    METHODS: Secondary analysis of a prospective observational study including 40 critically ill adults receiving intravenous insulin, mechanical ventilation and vasopressor therapy. Paired ABG and CGM values (n = 2946) were analyzed. The primary outcome was percentage absolute relative difference (ARD). Secondary outcomes were the proportions of CGM readings meeting ISO 15197:2013 and CLSI POCT12-A3 criteria. Multivariable generalized linear mixed models with patient-level random intercepts were fitted, applying B-splines for continuous covariates.
    RESULTS: Median (IQR) ARD was 10.8% (5.2-18.8) (mean ARD 12.7 [95% CI 10.7-15.3] %); 64.5% and 56.0% of readings met ISO and CLSI criteria, respectively. Sensor wear time (P < 0.001) and pH (P ≤ 0.02) were independently associated with ARD and both categorical accuracy metrics. Predicted ARD decreased, and the probability of meeting ISO/CLSI criteria increased, during the first 50 h after sensor insertion and then stabilized. The pH-accuracy relationships were approximately linear; in linear-term sensitivity analyses, each 0.1-unit increase in pH was associated with a 1.5 percentage-point higher ARD (P = 0.009) and 32% lower odds of meeting CLSI criteria (P = 0.001). NE-dose (P = 0.006) and ABG (P < 0.001) were independently associated with ISO-defined accuracy. Spline analyses suggested reduced accuracy at higher NE-doses (>0.6 µg/kg/min) and lower ABG (<5 mmol/L [<90 mg/dL]), although observations were limited in these ranges.
    CONCLUSIONS: In critically ill patients receiving mechanical ventilation and vasopressor therapy, CGM accuracy improves substantially with increasing sensor wear time and is independently associated with arterial pH. Early postinsertion sensor instability and acid-base disturbances appear to be important determinants of CGM performance in critical illness.
    Keywords:  continuous glucose monitoring; critical care; decision support; hypoglycaemia; insulin infusion; lactate; noradrenaline; tissue perfusion; vasopressor
    DOI:  https://doi.org/10.1177/15209156261479816
  10. J Diabetes Complications. 2026 Jul 17. pii: S1056-8727(26)00123-6. [Epub ahead of print]40(10): 109378
       BACKGROUND: Continuous Glucose Monitor (CGM) Time-in-Range (TIR) is a valuable glycemic metric, with TIR >70% linked to lower HbA1c. Less is known about TIR reliability with lower CGM wear-time.
    METHOD: This study examined the TIR-HbA1c association in 60 youth with type 1 diabetes (T1D) with ≥70% vs. <70% CGM wear-time. Pearson correlations between TIR and HbA1c were calculated within each wear-time group and compared using a Fisher r-to-z transformation.
    RESULTS: Correlations between TIR and HbA1c were significant in both wear time groups (≥70% r = -0.800, p < .001; <70% r = -0.404, p < .001), with the ≥70% group having a significantly stronger association (z = 3.15, p = .0016).
    CONCLUSION: Although the association was weaker among those with <70% wear-time, statistical significance suggests there may be utility in relying on lower wear-time data when needed.
    Keywords:  Adolescents; CGM wear-time; Continuous glucose monitoring; HbA1c; Time-in-range; Type 1 diabetes
    DOI:  https://doi.org/10.1016/j.jdiacomp.2026.109378
  11. Endocr J. 2026 Aug 18.
    REALJ Study Group
      Although randomized controlled trials have demonstrated the efficacy of real-time continuous glucose monitoring (rtCGM), evidence from routine clinical practice remains limited, particularly in Asian populations. This study aimed to evaluate the effectiveness and safety of rtCGM initiation in individuals with diabetes. This multicenter, single-arm, retrospective, observational study was conducted at 34 sites across Japan (Clinical trial registration: UMIN000054275). Adults ≥18 years of age with diabetes who began using the Dexcom G6 rtCGM system, had a baseline glycated hemoglobin (HbA1c) level ≥7.5%, and continued rtCGM for at least 26 weeks were included. Factors associated with changes in HbA1c levels were examined using multivariate linear regression models. Among 192 participants, the mean HbA1c levels at 26 weeks were significantly lower (8.62 ± 1.14% vs. 7.88 ± 1.16%, p < 0.001) than those at baseline, with a difference of -0.73 ± 1.03%. In the multivariate analysis, greater HbA1c reduction was independently associated with higher baseline HbA1c (β = -0.40; p < 0.001), longer CGM active time (β = -0.008; p = 0.043), and older age (β = -0.010; p = 0.012), whereas prior isCGM use was associated with smaller reductions (β = +0.28; p = 0.045). Sex was also independently associated with changes in HbA1c levels (p = 0.028). During the 26-week follow-up period, one patient (0.5%) experienced diabetic ketoacidosis and four individuals (2.1%) experienced severe hypoglycemia. rtCGM initiation was associated with significantly lower HbA1c levels after 26 weeks of rtCGM use. These findings support the efficacy and safety of the Dexcom G6 in routine clinical practice.
    Keywords:  Adult; Continuous glucose monitoring; Diabetic ketoacidosis; Glycemic control; Severe hypoglycemia
    DOI:  https://doi.org/10.1507/endocrj.EJ26-0183
  12. Diabetes Technol Ther. 2026 Aug 18. 15209156261479814
      To evaluate efficacy and safety of continuous glucose monitoring (CGM) and automated insulin delivery (AID) in infants. A retrospective multicenter study (13 centers) of 76 children diagnosed with antibody-positive type 1 diabetes before age 2. Outcomes at 12 months were compared between AID users (n = 47) and multiple daily injections (MDI)/SAP users (n = 29). AID systems included Medtronic 780 G (38%), Tandem Control-IQ (38%), and CamAPS FX (24%). CGM median wear time was 97.0% (93.3; 98.1). AID users achieved significantly higher TIR (65% vs. 56%, P = 0.041) and time in tight range (TITR) (42% vs 32.5%, P = 0.038). In multivariable regression, AID was the sole independent predictor of lower HbA1c (P = 0.035). Zero severe hypoglycemia (SH) events occurred in the AID group (vs. 7.1% in MDI/SAP). Use of CGM is safe in very young children, with AID systems proving superior to traditional therapy. This real-world evidence supports incorporating AID consideration into future international guidelines from the time of pediatric diagnosis.
    Keywords:  automated insulin delivery; continuous glucose monitoring; hypoglycemia; infants; time in range; type 1 diabetes
    DOI:  https://doi.org/10.1177/15209156261479814
  13. Diabet Med. 2026 Aug 18. e70448
       AIMS: Telemonitoring in type 2 diabetes (T2D) care has demonstrated positive trends in terms of glycaemic control. However, evidence regarding its impact on patient-reported outcomes, such as general and diabetes-specific quality of life (QoL), remains inconclusive. In particular, the effect of telemonitoring in people with insulin-treated T2D is underexplored. This study aimed to evaluate the effect of telemonitoring on general and diabetes-specific QoL compared with usual care in people with insulin-treated T2D.
    METHODS: Participants were randomised (1:1) to telemonitoring or usual care for 3 months. The primary outcomes were changes in the Short Form-12 Health Survey (SF-12) and the DAWN2 Impact of Diabetes Profile (DIDP). Telemonitoring included a continuous glucose monitor (CGM), a connected insulin pen, and an activity tracker. Data were monitored by hospital staff, who also provided regular telephone support. Usual care comprised a blinded connected insulin pen and a blinded CGM during the first and final 20 days, but their data were not monitored. ANCOVA compared groups for normally distributed data, with baseline scores as covariates. The Mann-Whitney U test was applied for non-normally distributed outcomes.
    RESULTS: A total of 331 participants were included (telemonitoring: n = 166; usual care: n = 165). No significant between-group differences were found in SF-12 scores for neither the physical (p = 0.102) nor mental component summary score (p = 0.566). The telemonitoring group showed a statistically significant improvement in DIDP compared with usual care (p = 0.015).
    CONCLUSIONS: Telemonitoring had no effect on general QoL but led to a statistically significant improvement in diabetes-specific QoL.
    Keywords:  continuous glucose monitoring; diabetes mellitus type 2; patient‐reported outcome measures; quality of life; telemedicine
    DOI:  https://doi.org/10.1111/dme.70448
  14. JBI Evid Synth. 2026 Aug 14.
       OBJECTIVE: This scoping review aimed to map the evidence on the use of diabetes technologies by primary school children (aged 6 to 12 years) with type 1 diabetes and their parents in primary school settings. Specifically, it aimed to identify the types of technologies used, who is responsible for managing and supporting their use, and the benefits and challenges associated with their use during the school day.
    INTRODUCTION: Technological advances in diabetes care have revolutionized the management of diabetes, but their integration into school settings introduces new challenges for children, parents, and school staff. Evidence about their use during the primary school day remains fragmented.
    ELIGIBILITY CRITERIA: Qualitative, quantitative, and mixed methods studies, as well as systematic reviews, that included children aged 6 to 12 years and/or their parents and focused on the use of diabetes technologies in the primary school environment were eligible for inclusion. Gray literature was also considered. Studies that did not include diabetes technology, primary school-age children and/or their parents, or the context of the primary school environment were excluded.
    METHODS: A search for relevant records was conducted in April 2025 across CINAHL Ultimate (EBSCOhost), Embase.com, MEDLINE (EBSCOhost), Web of Science Core Collection, and Google Scholar. Gray and unpublished literature were searched for in ProQuest Dissertations and Theses Global and Google Scholar. Two independent reviewers screened titles and abstracts and full-text sources. The findings are presented in tables, accompanied by a basic content analysis and a descriptive narrative summary based on the review questions.
    RESULTS: Twenty-three studies were included in this review: 15 qualitative studies, 4 quantitative studies, and 4 mixed-methods studies. Studies were conducted in multiple countries, including the United Kingdom, the United States, Australia, New Zealand, Denmark, Canada, Poland, Belgium, Turkey. There were also 2 multicountry sources. Publication years ranged from 2004 to 2025. Results from child and parent reports showed that continuous subcutaneous insulin infusion devices, continuous glucose monitoring, flash glucose monitoring, and hybrid closed-loop systems are being used by children in the primary school environment. These technologies are managed during the school day through a collaborative approach, involving the children, their parents, and various school personnel. The benefits of using diabetes technology in the primary school environment was identified across 4 main categories: i) improved school participation and academic engagement and social-emotional well-being; ii) increased independence, confidence, and self-management; iii) enhanced safety and monitoring; and iv) reduced burden on parents and school staff. The challenges were identified across 4 categories: i) device-related challenges; ii) social stigma and peer interaction challenges; iii) school personnel competency and training challenges; and iv) parental stress and family challenges.
    CONCLUSIONS: This scoping review offers insights into the use of diabetes technology during the primary school day from the perspectives of children and their parents. It highlights that diabetes technology can support children's inclusion, autonomy, and confidence during school. It also highlights the need for structured training for school personnel, clear role delineation, and supportive school policies to ensure the safe and sustainable use of technology.
    REVIEW REGISTRATION: OSF https://osf.io/fhw3x.
    Keywords:  children; diabetes technology; parents; primary schools; type 1 diabetes
    DOI:  https://doi.org/10.11124/JBIES-25-00511